Monthly Archives: May 2016

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(Excerpt from original post on the Taneja Group News Blog)

We’ve been writing recently about the hot, potentially inevitable, trend, towards a dense IT infrastructure in which components like CPU cores and disks are not only commoditized, but deployed in massive stacks or pools (with fast matrixing switches between them). Then a layered provisioning solution can dynamically compose any desired “physical” server or cluster out of those components. Conceptually this becomes the foundation for a bare-metal cloud. DriveScale today announces their agile architecture with this approach, aimed first at solving big data multi-cluster operational challenges.

(Excerpt from original post on the Taneja Group News Blog)

It’s time to start thinking about massive amounts of flash in the enterprise data center. I mean PBs of flash for the biggest, baddest, fastest data-driven applications out there. This amount of flash requires an HPC-capable storage solution brought down and packaged for enterprise IT management. Which is where Data Domain Networks (aka DDN) is stepping up. Perhaps too quietly, they have been hard at work pivoting their high-end HPC portfolio into the enterprise space. Today they are rolling out a massively scalable new flash-centric Flashscale 14KXi storage array that will help them offer complete, comprehensive single-vendor big data workflow solutions – from the fastest scratch through the biggest throughput parallel file systems into the largest distributed object storage archives.

(Excerpt from original post on the Taneja Group News Blog)

All you storage geeks and science fiction fans rejoice! If Cloud Constellation gets its way, you’ll soon be able to directly hybridize your dreary earthbound data center storage with actually above-the-clouds storage. Yep, protect your sensitive data by replicating it to true satellite storage. Only James Bond with a spare Shuttle would be able to hack those things. Just how far fetched is this idea?

(Excerpt from original post on the Taneja Group News Blog)

Last month NVIDIA, our favorite GPU vendor, dived into the converged appliance space. In fact we might call their new NVIDIA DGX-1 a hyperconverged supercomputer in a 4U box. Designed to support the application of GPU’s to Deep Learning (i.e. compute intensive deeply layered neural networks that need to train and run in operational timeframes over big data), this beast has 8 new Tesla P100 GPUs inside on an embedded NVLink mesh, pre-integrated with flash SSDs, decent memory, and an optimized container-hosting deep learning software stack. The best part? The price is surprisingly affordable, and can replace the 250+ server cluster you might otherwise need for effective Deep Learning.

An IT industry analyst article published by Infostor.

At Taneja Group we are seeing a major trend within IT to leverage server and server-side resources to the maximum extent possible. Servers themselves have become commodities, and dense memory, server-side flash, even compute power continue to become increasingly powerful and cost-friendly. Many datacenters already have a glut of CPU that will only increase with newer generations of faster, larger-cored chips, denser packaging and decreasing power requirements. Disparate solutions from in-memory databases (e.g. SAP HANA) to VMware’s NSX are taking advantage of this rich excess by separating out and moving functionality that used to reside in external devices (i.e. SANs and switches) up onto the server.

Within storage we see two hot trends – hyperconvergence and software defined – getting most of the attention lately. But when we peel back the hype, we find that both are really enabled by this vastly increasing server power – in particular server resources like CPU, memory and flash are getting denser, cheaper and more powerful to the point where they are capable of hosting sophisticated storage processing capabilities directly. Where traditional arrays built on fully centralized, fully shared hardware might struggle with advanced storage functions at scale, server-side storage tends to scale functionality naturally with co-hosted application workloads. The move towards “server-siding” everything is so talked about that it seems inevitable that traditional physical array architectures are doomed.

RT @TruthinIT: There's no cost of goods like a traditional NAS device where I've got disks I've got to pay for. And if I'm not using the data on those disks, I still got to pay for those disks. bit.ly/2BBX073@Nasuni@smworldbigdata

In 30 min I'm interviewing @Cohesity (and customer) on @TruthinIT about Mass Data Fragmentation. It's about having too many copies in about four or five different "dimensions", including cloud! Join us webcast (12.11.18) @ 1pmET (and there will be prizes) bit.ly/2PdqrQn